On-line learning of non-monotonic rules by simple perceptron

Jun-ichi Inoue; Hidetoshi Nishimori; Yoshiyuki Kabashima

doi:10.1088/0305-4470/30/11/012

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arXiv · cond-mat/9703020

On-line learning of non-monotonic rules by simple perceptron

Jun-ichi Inoue·Hidetoshi Nishimori·Yoshiyuki Kabashima

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Abstract

We study the generalization ability of a simple perceptron which learns unlearnable rules. The rules are presented by a teacher perceptron with a non-monotonic transfer function. The student is trained in the on-line mode. The asymptotic behaviour of the generalization error is estimated under various conditions. Several learning strategies are proposed and improved to obtain the theoretical lower bound of the generalization error.

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Jun-ichi Inoue, Hidetoshi Nishimori, Yoshiyuki Kabashima. 1997-03-03. On-line learning of non-monotonic rules by simple perceptron. https://doi.org/10.1088/0305-4470%2F30%2F11%2F012

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